Statistical analysis of power systems and application to load forecasting

Yakir Loewenstern; Liran Katzir; Doron Shmilovitz

doi:10.1109/EEEI.2014.7005879

Statistical analysis of power systems and application to load forecasting

Yakir Loewenstern, Liran Katzir, Doron Shmilovitz

School of Electrical Engineering

Tel Aviv University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

For many years, Load Forecasting (LF) has been an area of intense research. Most research has focused on short and long-term forecasting, with "short-term" generally meaning one hour in advance, to enable some power grid operations tasks. However, finer-grained prediction, at a resolution of minutes, can assist with other tasks, such as Power System State Estimation, and matching load to renewable energy generation in developing Smart Grids. To allow such ephemeral-term prediction with high accuracy, analysis of historical data sampled at high frequency is necessary. In this paper, we present statistical analysis based on three years' worth of real data obtained from the New York Independent System Operator (NYISO). The data is fine-grained, at a resolution of one sample per five minutes. The advantage of this data set is the ability to verify the applicability of our results to both large and small systems. The data and analysis presented in this paper can be used as a baseline for future LF and Smart Grid research.

Original language	English
Title of host publication	2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479959877
DOIs	https://doi.org/10.1109/EEEI.2014.7005879
State	Published - 2014
Event	2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 - Eilat, Israel Duration: 3 Dec 2014 → 5 Dec 2014

Publication series

Name	2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

Conference

Conference	2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
Country/Territory	Israel
City	Eilat
Period	3/12/14 → 5/12/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Load forecasting
Load modeling
Power systems
Smart Grid

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/EEEI.2014.7005879

Cite this

Loewenstern, Y., Katzir, L., & Shmilovitz, D. (2014). Statistical analysis of power systems and application to load forecasting. In 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 Article 7005879 (2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEEI.2014.7005879

Loewenstern, Yakir ; Katzir, Liran ; Shmilovitz, Doron. / Statistical analysis of power systems and application to load forecasting. 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. (2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014).

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title = "Statistical analysis of power systems and application to load forecasting",

abstract = "For many years, Load Forecasting (LF) has been an area of intense research. Most research has focused on short and long-term forecasting, with {"}short-term{"} generally meaning one hour in advance, to enable some power grid operations tasks. However, finer-grained prediction, at a resolution of minutes, can assist with other tasks, such as Power System State Estimation, and matching load to renewable energy generation in developing Smart Grids. To allow such ephemeral-term prediction with high accuracy, analysis of historical data sampled at high frequency is necessary. In this paper, we present statistical analysis based on three years' worth of real data obtained from the New York Independent System Operator (NYISO). The data is fine-grained, at a resolution of one sample per five minutes. The advantage of this data set is the ability to verify the applicability of our results to both large and small systems. The data and analysis presented in this paper can be used as a baseline for future LF and Smart Grid research.",

keywords = "Load forecasting, Load modeling, Power systems, Smart Grid",

author = "Yakir Loewenstern and Liran Katzir and Doron Shmilovitz",

note = "Publisher Copyright: {\textcopyright} Copyright 2015 IEEE All rights reserved.; 2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 ; Conference date: 03-12-2014 Through 05-12-2014",

year = "2014",

doi = "10.1109/EEEI.2014.7005879",

language = "الإنجليزيّة",

series = "2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014",

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address = "الولايات المتّحدة",

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Loewenstern, Y, Katzir, L & Shmilovitz, D 2014, Statistical analysis of power systems and application to load forecasting. in 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014., 7005879, 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014, Institute of Electrical and Electronics Engineers Inc., 2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014, Eilat, Israel, 3/12/14. https://doi.org/10.1109/EEEI.2014.7005879

Statistical analysis of power systems and application to load forecasting. / Loewenstern, Yakir; Katzir, Liran; Shmilovitz, Doron.
2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. 7005879 (2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Statistical analysis of power systems and application to load forecasting

AU - Loewenstern, Yakir

AU - Katzir, Liran

AU - Shmilovitz, Doron

PY - 2014

Y1 - 2014

N2 - For many years, Load Forecasting (LF) has been an area of intense research. Most research has focused on short and long-term forecasting, with "short-term" generally meaning one hour in advance, to enable some power grid operations tasks. However, finer-grained prediction, at a resolution of minutes, can assist with other tasks, such as Power System State Estimation, and matching load to renewable energy generation in developing Smart Grids. To allow such ephemeral-term prediction with high accuracy, analysis of historical data sampled at high frequency is necessary. In this paper, we present statistical analysis based on three years' worth of real data obtained from the New York Independent System Operator (NYISO). The data is fine-grained, at a resolution of one sample per five minutes. The advantage of this data set is the ability to verify the applicability of our results to both large and small systems. The data and analysis presented in this paper can be used as a baseline for future LF and Smart Grid research.

AB - For many years, Load Forecasting (LF) has been an area of intense research. Most research has focused on short and long-term forecasting, with "short-term" generally meaning one hour in advance, to enable some power grid operations tasks. However, finer-grained prediction, at a resolution of minutes, can assist with other tasks, such as Power System State Estimation, and matching load to renewable energy generation in developing Smart Grids. To allow such ephemeral-term prediction with high accuracy, analysis of historical data sampled at high frequency is necessary. In this paper, we present statistical analysis based on three years' worth of real data obtained from the New York Independent System Operator (NYISO). The data is fine-grained, at a resolution of one sample per five minutes. The advantage of this data set is the ability to verify the applicability of our results to both large and small systems. The data and analysis presented in this paper can be used as a baseline for future LF and Smart Grid research.

KW - Load forecasting

KW - Load modeling

KW - Power systems

KW - Smart Grid

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DO - 10.1109/EEEI.2014.7005879

M3 - منشور من مؤتمر

T3 - 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

BT - 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

Y2 - 3 December 2014 through 5 December 2014

ER -

Loewenstern Y, Katzir L, Shmilovitz D. Statistical analysis of power systems and application to load forecasting. In 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. 7005879. (2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014). doi: 10.1109/EEEI.2014.7005879

Statistical analysis of power systems and application to load forecasting

Abstract

Publication series

Conference

UN SDGs

Keywords

All Science Journal Classification (ASJC) codes

Access to Document

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